mirror of https://github.com/vladmandic/human
88 lines
2.9 KiB
JavaScript
88 lines
2.9 KiB
JavaScript
const log = require('@vladmandic/pilogger');
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const fs = require('fs');
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const process = require('process');
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// for Node, `tfjs-node` or `tfjs-node-gpu` should be loaded before using Human
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const tf = require('@tensorflow/tfjs-node'); // or const tf = require('@tensorflow/tfjs-node-gpu');
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// load specific version of Human library that matches TensorFlow mode
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const Human = require('../dist/human.node.js').default; // or const Human = require('../dist/human.node-gpu.js').default;
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let human = null;
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const myConfig = {
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backend: 'tensorflow',
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console: true,
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videoOptimized: false,
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async: false,
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face: {
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detector: { modelPath: 'file://models/faceboxes.json' }, // cannot use blazeface in nodejs due to missing required kernel function in tfjs-node
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mesh: { modelPath: 'file://models/facemesh.json' },
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iris: { modelPath: 'file://models/iris.json' },
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age: { modelPath: 'file://models/age-ssrnet-imdb.json' },
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gender: { modelPath: 'file://models/gender-ssrnet-imdb.json' },
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emotion: { modelPath: 'file://models/emotion-large.json' },
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},
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body: { modelPath: 'file://models/posenet.json' },
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hand: {
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detector: { modelPath: 'file://models/handdetect.json' },
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skeleton: { modelPath: 'file://models/handskeleton.json' },
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},
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};
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async function init() {
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// wait until tf is ready
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await tf.ready();
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// create instance of human
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human = new Human(myConfig);
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// pre-load models
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await human.load();
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}
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async function detect(input) {
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// read input image file and create tensor to be used for processing
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const buffer = fs.readFileSync(input);
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const decoded = human.tf.node.decodeImage(buffer);
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const casted = decoded.toFloat();
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const image = casted.expandDims(0);
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decoded.dispose();
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casted.dispose();
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// image shape contains image dimensions and depth
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log.state('Processing:', image.shape);
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// run actual detection
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const result = await human.detect(image, myConfig);
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// dispose image tensor as we no longer need it
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image.dispose();
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// print data to console
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log.data(result);
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}
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async function test() {
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// test with embedded face image
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log.state('Processing embedded warmup image: face');
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myConfig.warmup = 'face';
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const resultFace = await human.warmup(myConfig);
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log.data('Face: ', resultFace.face);
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// test with embedded full body image
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log.state('Processing embedded warmup image: full');
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myConfig.warmup = 'full';
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const resultFull = await human.warmup(myConfig);
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log.data('Body:', resultFull.body);
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log.data('Hand:', resultFull.hand);
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log.data('Gesture:', resultFull.gesture);
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}
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async function main() {
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log.info('NodeJS:', process.version);
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await init();
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if (process.argv.length !== 3) {
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log.warn('Parameters: <input image> missing');
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await test();
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} else if (!fs.existsSync(process.argv[2])) {
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log.error(`File not found: ${process.argv[2]}`);
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} else {
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await detect(process.argv[2]);
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}
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}
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main();
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